Information distribution is needed in various scenarios to facilitate business operations. Typically, information is gathered from a plurality of sources, such as user and product databases, and sent to a number of devices, such as computer terminals and personal digital assistants, connected to a distribution system. The distribution system, generally, identifies sets or clusters within a chunk of data and distributes the data to individual devices. The distribution system typically includes a data definition including data objects or business objects. Data objects usually have a hierarchical structure where every level in the hierarchy is a node. Each node typically includes a number of fields. Data is packed into this hierarchical structure as data object instances. The data is generally distributed to a user in the form of data object instances.
Dependencies exist between one or more data objects in various scenarios and there is a need for distributing one or more dependent data object instances to the user if a parent data object is to be distributed to the user. These dependencies between data objects are typically captured as associations. Each field in a node generally includes one or more keys that uniquely identify the field. A referring node of a data object generally includes all the keys of a referred node there by creating a 1:1 relationship from the referring node perspective. But there are scenarios where the referring node includes only a subset of keys of the referred node resulting in a 1:N relationship. In the currently existing distribution systems, the 1:N relationships are typically handled by the distribution system. A data set for distribution is calculated at runtime by the distribution system on receiving distribution requests from the user. Thus the complexity of the 1:N relationships and the runtime calculation of the data set results is an increased load upon the distribution system affecting the distribution system performance.